Vehicle fault diagnosis and analysis based on augmented design failure mode and effect analysis (dfmea) data

ABSTRACT

A system and method of performing fault diagnosis and analysis for one or more vehicles. The method includes: obtaining design failure mode and effect analysis (DFMEA) data that specifies a plurality of failure modes; receiving diagnostic association data; receiving vehicle operation signals association data; generating augmented DFMEA data that indicates a causal relationship between the diagnostic data and the first set of failure modes, and that indicates a causal relationship between the vehicle operation signals data and the second set of failure modes, wherein the augmented DFMEA data is generated based on the DFMEA data, the diagnostic association data, and the vehicle operation signals association data; and performing fault diagnosis and analysis for the one or more vehicles using the augmented DFMEA data.

INTRODUCTION

The present invention relates to performing fault diagnosis and analysisfor one or more vehicles based on augmented design failure mode andeffect analysis (DFMEA) data.

Vehicles include hardware and software capable of obtaining andprocessing various information, including information that is obtainedby vehicle system modules (VSMs). Service technicians can diagnosecertain vehicle problems using an onboard diagnostic (OBD) tool, such asa tool that plugs into or connects to an OBD II port of a vehicle. Also,as a part of manufacturing the vehicle, design failure mode and effectanalysis (DFMEA) data is generated.

SUMMARY

According to one aspect of the invention, there is provided a method ofperforming fault diagnosis and analysis for one or more vehicles. Themethod includes: obtaining design failure mode and effect analysis(DFMEA) data, wherein the DFMEA data specifies a plurality of failuremodes; receiving diagnostic association data, wherein the diagnosticassociation data specifies, for each of a first set of the plurality offailure modes, diagnostic data that is to be associated with the failuremode; receiving vehicle operation signals association data, wherein thevehicle operation signals association data specifies, for each of asecond set of the plurality of failure modes, vehicle operation signalsdata that is to be associated with the failure mode; generatingaugmented DFMEA data that indicates a causal relationship between thediagnostic data and the first set of failure modes, and that indicates acausal relationship between the vehicle operation signals data and thesecond set of failure modes, wherein the augmented DFMEA data isgenerated based on the DFMEA data, the diagnostic association data, andthe vehicle operation signals association data; and performing faultdiagnosis and analysis for the one or more vehicles using the augmentedDFMEA data.

According to various embodiments, this method may further include anyone of the following features or any technically-feasible combination ofsome or all of these features:

-   -   the DFMEA data includes or is based on a first DFMEA document        that is generated as a part of designing, developing,        manufacturing, and/or testing a first subsystem of the one or        more vehicles, wherein the DFMEA data includes or is based on a        second DFMEA document that is generated as a part of designing,        developing, manufacturing, and/or testing a second subsystem of        the one or more vehicles;    -   the plurality of failure modes includes a plurality of first        subsystem failure modes and a plurality of second subsystem        failure modes, wherein the plurality of first subsystem failure        modes specifies failure modes pertaining to the first subsystem,        and wherein the plurality of second subsystem failure modes        specifies failure modes pertaining to the second subsystem;    -   the augmented DFMEA data includes a first augmented DFMEA        document and a second augmented DFMEA document, wherein the        first augmented DFMEA document indicates the causal relationship        between the diagnostic data and a third set of failure modes,        wherein the third set of failure modes are those failure modes        that are a part of the first set of failure modes and the first        subsystem failure modes, wherein the first augmented DFMEA        document indicates the causal relationship between the vehicle        operation signals data and a fourth set of failure modes, and        wherein the fourth set of failure modes are those failure modes        that are a part of the second set of failure modes and the first        subsystem failure modes;    -   the second augmented DFMEA document indicates the causal        relationship between the diagnostic data and a fifth set of        failure modes, wherein the fifth set of failure modes are those        failure modes that are a part of the first set of failure modes        and the second subsystem failure modes, wherein the second        augmented DFMEA document indicates the causal relationship        between the vehicle operation signals data and a sixth set of        failure modes, and wherein the sixth set of failure modes are        those failure modes that are a part of the second set of failure        modes and the second subsystem failure modes;    -   generating a dependency model based on the augmented DFMEA data,        wherein the dependency model captures causal relationship(s)        between the first subsystem failure modes and the second        subsystem failure modes, and wherein the causal relationship(s)        are identified based on the first augmented DFMEA document and        the second augmented DFMEA document;    -   the diagnostics association data is received from a first        technical specialist at a first computer, and wherein the        vehicle operation signals association data is received from a        second technical specialist at a second computer;    -   the fault diagnosis and analysis includes generating an        artificial intelligence (AI) classifier based on the augmented        DFMEA data;    -   the fault diagnosis and analysis includes executing an AI        computer application to diagnose the one or more vehicles based        on observed diagnostic data and/or observed vehicle operation        signals data pertaining to the one or more vehicles, and wherein        the AI computer application is configured to use the AI        classifier to diagnose the one or more vehicles;    -   sending a message to at least one of the one or more vehicles,        wherein the message indicates a particular failure mode of the        plurality of failure modes that is identified based on the        diagnosis performed using the AI computer application; and/or    -   the fault diagnosis and analysis includes determining whether        each of the plurality of failure modes are isolatable from one        another.

According to another aspect of the invention, there is provided a methodof performing fault diagnosis and analysis for one or more vehicles. Themethod includes: obtaining design failure mode and effect analysis(DFMEA) data, wherein the DFMEA data specifies a plurality of failuremodes including first subsystem failure modes and second subsystemfailure modes; receiving diagnostic association data, wherein thediagnostic association data specifies, for each of a first set of theplurality of failure modes, one or more diagnostic trouble code(s)(DTC(s)) that are to be associated with the failure mode; receivingvehicle operation signals association data, wherein the vehicleoperation signals association data specifies, for each of a second setof the plurality of failure modes, vehicle operation signals data thatis to be associated with the failure mode; generating augmented DFMEAdata that indicates the DTC(s) that are observable at the one or morevehicles when the one or more vehicles are experiencing any failuremode(s) of the first set of failure modes, and that indicates thevehicle operation signals data that is observable at the one or morevehicles when the one or more vehicles are experiencing any failuremode(s) of the second set of failure modes, wherein the augmented DFMEAdata is generated based on the DFMEA data, the diagnostic associationdata, and the vehicle operation signals association data; generating adependency model based on the augmented DFMEA data, wherein thedependency model indicates causal relationships between the firstsubsystem failure modes and the second subsystem failure modes; andperforming fault diagnosis and analysis for the one or more vehiclesusing the augmented DFMEA data.

According to various embodiments, this method may further include anyone of the following features or any technically-feasible combination ofsome or all of these features:

-   -   the fault diagnosis and analysis includes: obtaining observed        diagnostic data and observed vehicle operation signals data        pertaining to at least one of the one or more vehicles, and        identifying a failure mode of the at least one vehicle by        comparing the observed diagnostic data to diagnostic data as        indicated in the dependency model and by comparing the observed        vehicle operation signals data to vehicle operation signals data        as indicated in the dependency model;    -   wherein a first portion of the diagnostics association data is        received from a first technical specialist at a first computer        and a second portion of the diagnostics association data is        received from a second technical specialist at a second        computer; and/or    -   a first portion of the vehicle operation signals association        data is received from a third technical specialist at a third        computer and a second portion of the vehicle operation signals        association data is received from a fourth technical specialist        at a fourth computer.

According to yet another aspect of the invention, there is provided avehicle fault diagnosis and analysis system. The vehicle fault diagnosisand analysis system includes: one or more computers each having aprocessor; and memory storing computer instructions that are executableby the one or more computers, wherein the memory is communicativelycoupled to the one or more computers; wherein, when the computerinstructions are executed by the one or more computers, the vehiclefault diagnosis and analysis system: (i) obtains augmented designfailure mode and effect analysis (DFMEA) data that indicates diagnosticdata that is observable at one or more vehicles when the one or morevehicles are experiencing any failure mode(s) of a first set of failuremodes, and that indicates vehicle operation signals data that isobservable at the one or more vehicles when the one or more vehicles areexperiencing any failure mode(s) of a second set of failure modes,wherein the augmented DFMEA data is generated based on DFMEA data,diagnostic association data, and vehicle operation signals associationdata; and (ii) performs fault diagnosis and analysis for the one or morevehicles using the augmented DFMEA data.

According to various embodiments, this vehicle fault diagnosis andanalysis system may further include any one of the following features orany technically-feasible combination of some or all of these features:

-   -   the augmented DFMEA data is generated by a DFMEA augmentation        application that is executable by one or more remote computers,        wherein, when the DFMEA augmentation application is executed,        the one or more remote computers: (a) obtain the DFMEA data,        wherein the DFMEA data specifies a plurality of failure modes        including the first set of failure modes and the second set of        failure modes; (b) receive the diagnostic association data,        wherein the diagnostic association data specifies, for each of        the first set of failure modes, one or more diagnostic trouble        code(s) (DTC(s)) that are to be associated with the failure        mode; (c) receive the vehicle operation signals association        data, wherein the vehicle operation signals association data        specifies, for each of the second set of failure modes, vehicle        operation signals data that is to be associated with the failure        mode; (d) generate the augmented DFMEA data; and (e) provide the        augmented DFMEA data to the one or more computers of the vehicle        fault diagnosis and analysis system;    -   the one or more remote computers are separate from the one or        more computers of the vehicle fault diagnosis and analysis        system; and/or    -   the vehicle fault diagnosis and analysis system is controlled by        an original equipment manufacturer (OEM) of the one or more        vehicles, wherein the DFMEA augmentation application is provided        by the OEM to a supplier that provides parts to the OEM for the        one or more vehicles, and wherein the supplier controls the one        or more remote computers.

BRIEF DESCRIPTION OF THE DRAWINGS

One or more embodiments of the invention will hereinafter be describedin conjunction with the appended drawings, wherein like designationsdenote like elements, and wherein:

FIG. 1 is a block diagram depicting an embodiment of a communicationssystem that is capable of utilizing the method disclosed herein;

FIG. 2 is a flowchart of an embodiment of a method of performing faultdiagnosis and analysis for one or more vehicles; and

FIG. 3 is a flowchart of another embodiment of a method of performingfault diagnosis and analysis for one or more vehicles.

DETAILED DESCRIPTION

The system and method described below enables fault diagnosis andanalysis to be performed for one or more vehicles based on augmenteddesign failure mode and effect analysis (DFMEA) data that is generated.In many embodiments, DFMEA data pertaining to a vehicle subsystem, VSM,or other portions of the vehicle is obtained and then supplemented oraugmented with diagnostic data and vehicle operation signals data. Thediagnostic database includes information or data pertaining todiagnostics of one or more vehicles, and can include diagnostic troublecodes (DTCs) and/or other diagnostic information, such as various othererror or failure data or indicators. The vehicle operation signals datais information or data pertaining to vehicle operation signals, whichare electronic signals that are used as a part of normal vehicleoperation. In many embodiments, the method includes generating augmentedDFMEA data based on diagnostic association data, which provides for (orindicates) an association between certain diagnostic data (e.g., DTC(s))and failure modes of the DFMEA, and based on vehicle operation signalsassociation data, which provides for (or indicates) an associationbetween certain vehicle operation signals data (e.g., the presence ofparticular values of vehicle operation signals) and failure modes of theDFMEA. For example, these associations can indicate that certaindiagnostic data (e.g., DTC(s)) and/or certain vehicle operation signalsindicate the presence of a particular failure mode as specified in theDFMEA data.

As mentioned above, the augmented DFMEA data can be used for performingfault diagnosis and analysis for one or more vehicles. As used herein,the term “fault diagnosis and analysis” includes fault diagnosis, faultanalysis, or both. As an example of fault diagnosis, the augmented DFMEAdata can be used as a part of an artificial intelligence (AI) computerapplication that diagnosis one or more vehicles based on diagnostic datareceived from the vehicle and/or vehicle operation signals data receivedfrom the vehicle. The augmented DFMEA data can be used to develop,define, or otherwise generate an AI classifier that is used as a part ofthe AI computer application. As an example of fault analysis, theaugmented DFMEA data can be analyzed or inspected to determine whethereach of the failure modes are isolatable from one another based on thediagnostic data and the vehicle operation signals data. For example, iftwo failure modes of the augmented DFMEA data are indicated by the samecombination of diagnostic data and vehicle operation signals data, thenthe two failures modes are considered to be not isolatable from oneanother—that is, when the two failure modes have the same diagnosticassociation data and vehicle operation signals association data, thenthese two failure modes can be considered non-isolatable. The results ofthis analysis can be provided as feedback for developing or updatingfuture vehicle subsystems, VSMs, or other vehicle components. Otherfault diagnosis and analysis techniques, applications, orimplementations can certainly be used, as those provided herein aremerely exemplary.

In at least one embodiment, a DFMEA document (or other DFMEA data) maybe developed separately for each subsystem of a vehicle and, thus, theremay be a plurality of DFMEA documents for a particular vehicle. Each ofthese DFMEA documents can be augmented using the method below so thatthe failure modes of the DFMEA document is associated with diagnosticdata and/or vehicle operation signals data. Furthermore, once theplurality of augmented DFMEA documents are generated or otherwiseobtained, a dependency model can be generated that captures causalrelationship(s) between the failure modes of the various subsystems,along with diagnostic data and/or vehicle operation signals data. Thedependency model can thus indicate whether certain diagnosticinformation (e.g., DTC(s)) relating to a first subsystem is indicativeof a particular failure mode of a second subsystem where the firstsubsystem and the second subsystem are a part of the same vehicle, butare different from one another.

For example, in one embodiment, the first subsystem may be a fueldelivery subsystem of the vehicle and the second subsystem may be an airintake subsystem of the vehicle. The DTCs P0171 and P0174 may befirst-subsystem DTCs (or, more generally, first subsystem diagnosticdata) and can be specified in a first DFMEA document as being indicativeof a first failure mode of the first subsystem. The DTCs P0101, P0106,P0171, and P0174 may be second-subsystem DTCs (or, more generally,second subsystem diagnostic data) and can be specified in a second DFMEAdocument as being indicative of a first failure mode of the secondsubsystem. A dependency model (or other dependency data) can begenerated by merging each of the plurality of augmented DFMEA documents(or other data). The dependency model can thus provide informationconcerning how a failure mode of a first subsystem may actually be thecause of a failure mode of another subsystem. In the example above, thedependency model can indicate that the combination of DTCs P0101, P0106,P0171, and P0174 indicate the occurrence of the first failure mode ofthe second subsystem and that the DTCs P0171 and P0174 indicate theoccurrence of the first failure mode of the first subsystem. Thus, whenthe system observes the DTCs P0101, P0106, P0171, and P0174, this mayindicate that the failure of the vehicle is due to the second subsystemand not due to a failure of the first subsystem. In some embodiments,without this dependency model, the presence of the DTCs P0171 and P0174may indicate that there is a problem with the fuel delivery subsystem asthe causal link between the first failure mode and the DTCs P0171 andP0174 may not be available or specified in the first subsystem augmentedDFMEA document or other data.

With reference to FIG. 1, there is shown an operating environment thatcomprises a communications system 10 and that can be used to implementthe method disclosed herein. Communications system 10 generally includesa vehicle 12 with a wireless communications device 30 and other VSMs22-66, a constellation of global navigation satellite system (GNSS)satellites 68, one or more wireless carrier systems 70, a landcommunications network 76, one or more remote computers 78, and avehicle backend services facility 80. It should be understood that thedisclosed method can be used with any number of different systems and isnot specifically limited to the operating environment shown here. Also,the architecture, construction, setup, and general operation of thesystem 10 and its individual components are generally known in the art.Thus, the following paragraphs simply provide a brief overview of onesuch communications system 10; however, other systems not shown herecould employ the disclosed methods as well.

Wireless carrier system 70 may be any suitable cellular telephonesystem. Carrier system 70 is shown as including a cellular tower 72;however, the carrier system 70 may include one or more of the followingcomponents (e.g., depending on the cellular technology): cellulartowers, base transceiver stations, mobile switching centers, basestation controllers, evolved nodes (e.g., eNodeBs), mobility managemententities (MMEs), serving and PGN gateways, etc., as well as any othernetworking components required to connect wireless carrier system 70with the land network 76 or to connect the wireless carrier system withuser equipment (UEs, e.g., which can include telematics equipment invehicle 12). Carrier system 70 can implement any suitable communicationstechnology, including GSM/GPRS technology, CDMA or CDMA2000 technology,LTE technology, etc. In general, wireless carrier systems 70, theircomponents, the arrangement of their components, the interaction betweenthe components, etc. is generally known in the art.

Apart from using wireless carrier system 70, a different wirelesscarrier system in the form of satellite communication can be used toprovide uni-directional or bi-directional communication with thevehicle. This can be done using one or more communication satellites(not shown) and an uplink transmitting station (not shown).Uni-directional communication can be, for example, satellite radioservices, wherein programming content (news, music, etc.) is received bythe uplink transmitting station, packaged for upload, and then sent tothe satellite, which broadcasts the programming to subscribers.Bi-directional communication can be, for example, satellite telephonyservices using the one or more communication satellites to relaytelephone communications between the vehicle 12 and the uplinktransmitting station. If used, this satellite telephony can be utilizedeither in addition to or in lieu of wireless carrier system 70.

Land network 76 may be a conventional land-based telecommunicationsnetwork that is connected to one or more landline telephones andconnects wireless carrier system 70 to remote computers 78 and vehiclebackend services facility 80. For example, land network 76 may include apublic switched telephone network (PSTN) such as that used to providehardwired telephony, packet-switched data communications, and theInternet infrastructure. One or more segments of land network 76 couldbe implemented through the use of a standard wired network, a fiber orother optical network, a cable network, power lines, other wirelessnetworks such as wireless local area networks (WLANs), or networksproviding broadband wireless access (BWA), or any combination thereof.

Remote computers 78 (only one shown) can be some of a number ofcomputers accessible via a private or public network such as theInternet. In one embodiment, each such remote computer 78 can be usedfor one or more purposes, such as for receiving diagnostic associationdata and/or vehicle operation signals association data that can be usedto generate augmented DFMEA data. Other such accessible computers 78 canbe, for example: a server for providing navigational services to aplurality of vehicles and other electronic network computing devices; aservice center computer where diagnostic information and other vehicledata can be uploaded from the vehicle; a client computer used by thevehicle owner or other subscriber for such purposes as accessing orreceiving vehicle data or to setting up or configuring subscriberpreferences or controlling vehicle functions; a car sharing server whichcoordinates registrations from a plurality of users who request to use avehicle as part of a car sharing service; or a third party repository toor from which vehicle data or other information is provided, whether bycommunicating with the vehicle 12, backend facility 80, or both. Acomputer 78 can also be used for providing Internet connectivity such asDNS services or as a network address server that uses DHCP or othersuitable protocol to assign an IP address to vehicle 12.

Vehicle backend services facility 80 is a backend facility and islocated at a physical location that is located remotely from vehicle 12.The vehicle backend services facility 80 (or “backend facility 80” forshort) may be designed to provide the vehicle electronics 20 with anumber of different system back-end functions through use of one or moreelectronic servers 82 and, in some cases, may provide navigation-relatedservices to a plurality of vehicles. The vehicle backend servicesfacility 80 includes vehicle backend services servers 82 and databases84, which may be stored on a plurality of memory devices. Vehiclebackend services facility 80 may include any or all of these variouscomponents and, preferably, each of the various components are coupledto one another via a wired or wireless local area network. Backendfacility 80 may receive and transmit data via a modem connected to landnetwork 76. Data transmissions may also be conducted by wirelesssystems, such as IEEE 802.11x, GPRS, and the like. Those skilled in theart will appreciate that, although only one backend facility 80 and oneremote computer 78 are depicted in the illustrated embodiment of FIG. 1,numerous remote facilities 80 and/or remote computers 78 may be used.Moreover, a plurality of backend facilities 80 and/or remote computers78 can be geographically distributed, and can each coordinateinformation and services with one another, as those skilled in the artwill appreciate.

Servers 82 can be computers or other computing devices that include atleast one processor and that include memory. The processors can be anytype of device capable of processing electronic instructions including,for example, microprocessors, microcontrollers, host processors,controllers, vehicle communication processors, and application specificintegrated circuits (ASICs). The processors can be dedicated processorsused only for servers 82 or can be shared with other systems. The atleast one processor can execute various types of digitally-storedinstructions, such as software or firmware, which enable the servers 82to provide a wide variety of services. In one embodiment, the servers 82can carry out a DFMEA augmentation application that can generate orotherwise augment DFMEA data. Additionally or alternatively, the servers82 can carry out a vehicle fault diagnosis and analysis application,which performs fault diagnosis and analysis for one or more vehicles.The DFMEA augmentation application and the vehicle fault diagnosis andanalysis application can be embodied in software, which may be stored incomputer-readable memory.

The computer-readable memory can be any suitable computer-readablemedium, such as non-transitory, computer-readable memory. For example,the memory can be any of a number of different types of RAM(random-access memory, including various types of dynamic RAM (DRAM) andstatic RAM (SRAM)), ROM (read-only memory), solid-state drives (SSDs)(including other solid-state storage such as solid state hybrid drives(SSHDs)), hard disk drives (HDDs), and/or magnetic or optical discdrives. For network communications (e.g., intra-network communications,inter-network communications including Internet connections), theservers can include one or more network interface cards (NICs)(including wireless NICs (WNICs)) that can be used to transport data toand from the computers. These NICs can allow the one or more servers 82to connect with one another, databases 84, or other networking devices,including routers, modems, and/or switches. In one particularembodiment, the NICs (including WNICs) of servers 82 may allow SRWCconnections to be established and/or may include Ethernet (IEEE 802.3)ports to which Ethernet cables may be connected to that can provide fora data connection between two or more devices. Backend facility 80 caninclude a number of routers, modems, switches, or other network devicesthat can be used to provide networking capabilities, such as connectingwith land network 76 and/or wireless carrier system 70.

Databases 84 can be stored on a plurality of memory, such as a poweredtemporary memory or any suitable non-transitory, computer-readablemedium. For example, the memory can be any of a number of differenttypes of RAM (random-access memory, including various types of dynamicRAM (DRAM) and static RAM (SRAM)), ROM (read-only memory), solid-statedrives (SSDs) (including other solid-state storage such as solid statehybrid drives (SSHDs)), hard disk drives (HDDs), and/or magnetic oroptical disc drives. One or more databases at the backend facility 80can store various information and can include a DFMEA database, adiagnostic database, a vehicle operation signals database, and othervehicle information database(s).

The DFMEA database can include various information or data pertaining toDFMEA of various subsystems of the vehicle. The DFMEA data can includeDFMEA documents or files, which can be embodied in various formats thatare consumable or readable by one or more computer applications. In oneembodiment, the DFMEA documents or files (referred to collectively as“DFMEA documents”) can be Microsoft Excel™°documents, Microsoft Word™documents, comma separated value (CSV) documents, other delimiter-baseddocuments, etc. The DFMEA database can be a single database, or can bemany databases. For example, certain automotive suppliers may provideparts to a vehicle original equipment manufacturer (OEM), and theseautomotive suppliers can develop and store DFMEA data in their own DFMEAdatabase or memory. This supplier DFMEA data can be provided to thevehicle OEM, which can (in some embodiments) manage or control thebackend facility 80.

The diagnostic database includes diagnostic data, which includesinformation or data pertaining to diagnostics of one or more vehicles,and can include DTCs and/or other diagnostic information, such asvarious other error or failure data or indicators. The DTCs arediagnostic trouble codes, and can include those codes defined under theSociety of Automotive Engineers (SAE) standard J1979 and InternationalStandard Organization (ISO) 15031-5. The diagnostic database can includedescriptive information concerning each of the possible DTCs for aparticular vehicle or vehicle model, such as a description of what agiven DTC indicates when detected at the vehicle. The diagnosticdatabase can also include historical diagnostic data from a plurality ofvehicles, such as a fleet of vehicles having a common OEM. Thehistorical diagnostic data can include historical DTC data, which isdata that indicates one or more DTCs that were detected at a vehicle.This historical DTC data (or other historical diagnostic data) can beassociated with a time indicator (e.g., a timestamp) representing thetime of detecting the DTC (or other time associated with the DTC), alocation representing the location of detecting the DTC (or otherlocation associated with the DTC), and/or other information. Also, insome embodiments, the diagnostic database can include diagnosticassociation data that is received or otherwise obtained as a part ofembodiments of the method discussed below. In other embodiments, thediagnostic association data can be stored in another database.

The vehicle operation signals database includes vehicle operationsignals data, which is information or data pertaining to vehicleoperation signals, which are electronic signals that are used as a partof normal vehicle operation. The vehicle operation signals database caninclude descriptions of a plurality of vehicle operation signals for aparticular vehicle or vehicle model, such as a description of what agiven vehicle operation signal indicates when detected at the vehicleand/or what a given value (or one or more values (including one or moreranges of values)) of a particular vehicle operation signal indicates.The vehicle operation signals database can also include historicalvehicle operation signals data, which is data that indicates one or morevehicle operation signals that were detected at a vehicle. Thishistorical vehicle operation signals data can be associated with a timeindicator (e.g., a timestamp) representing the time of detecting thevehicle operation signal (or other time associated with the vehicleoperation signal), a location representing the location of detecting thevehicle operation signal (or other location associated with the vehicleoperation signal), and/or other information. Also, in some embodiments,the vehicle operation signals database can include vehicle operationsignals association data that is received or otherwise obtained as apart of embodiments of the method discussed below. In other embodiments,the vehicle operation signals association data can be stored in anotherdatabase.

The historical vehicle operation signals data and the historicaldiagnostic data can be associated with one another based on the timeindicators, event indicators (i.e., indicators that identify an event(e.g. a time and location for a particular vehicle)), locationindicators, etc. This association can be implemented bycross-referencing historical vehicle operation signals data in thevehicle operation signals database with the historical diagnostic datain the diagnostic database. In other embodiments, the historical vehicleoperation signals data and the historical diagnostic data can beincluded in a single database. Also, those skilled in the art willappreciate that many various structures can be used for the databases84.

Vehicle 12 is depicted in the illustrated embodiment as a passenger car,but it should be appreciated that any other vehicle includingmotorcycles, trucks, sports utility vehicles (SUVs), recreationalvehicles (RVs), marine vessels, aircraft, etc., can also be used. Someof the vehicle electronics 20 are shown generally in FIG. 1 and includea global navigation satellite system (GNSS) receiver 22, body controlmodule or unit (BCM) 24, engine control module (ECM) 26, other vehiclesystem modules (VSMs) 28, a wireless communications device 30,vehicle-user interfaces 50-56, first subsystem 40, and second subsystem60. In the illustrated embodiment, the vehicle 12 is an internalcombustion engine (ICE) vehicle. However, in other embodiments, thevehicle 12 can be a hybrid (e.g., a plug-in hybrid electric vehicle(PHEV)) or an electric vehicle. Some or all of the different vehicleelectronics 20 may be connected for communication with each other viaone or more communication buses, such as bus 58. Communications bus 58provides the vehicle electronics with network connections using one ormore network protocols. Examples of suitable network connections includea controller area network (CAN), a media oriented system transfer(MOST), a local interconnection network (LIN), a local area network(LAN), and other appropriate connections such as Ethernet or others thatconform with known ISO, SAE, and IEEE standards and specifications, toname but a few. In other embodiments, any one or more of the VSMs cancommunicate using a wireless network and can include suitable hardware,such as short-range wireless communications (SRWC) circuitry. Of course,any suitable combination of these communication techniques can be usedas well.

The vehicle 12 can include numerous vehicle system modules (VSMs) aspart of vehicle electronics 20, such as the GNSS receiver 22, BCM 24,ECM 26, wireless communications device 30, vehicle-user interfaces50-56, first subsystem VSMs 42-46, and second subsystem VSMs 62-66, aswill be described in detail below. The vehicle 12 can also include otherVSMs 28 in the form of electronic hardware components that are locatedthroughout the vehicle and, which may receive input from one or moresensors and use the sensed input to perform diagnostic, monitoring,control, reporting, and/or other functions. Each of the VSMs 28 isconnected by communications bus 58 to the other VSMs, as well as to thewireless communications device 30. One or more VSMs 28 may periodicallyor occasionally have their software or firmware updated and, in someembodiments, such vehicle updates may be over the air (OTA) updates thatare received from a computer 78 or backend facility 80 via land network76 and communications device 30. As is appreciated by those skilled inthe art, the above-mentioned VSMs are only examples of some of themodules that may be used in vehicle 12, as numerous others are alsopossible.

Global navigation satellite system (GNSS) receiver 22 receives GNSSsignals from a constellation of GNSS satellites 68. The GNSS receiver 22can be configured to comply with and/or operate according to particularregulations or laws of a given geopolitical region (e.g., country). TheGNSS receiver 22 can be configured for use with various GNSSimplementations, including global positioning system (GPS) for theUnited States, BeiDou Navigation Satellite System (BDS) for China,Global Navigation Satellite System (GLONASS) for Russia, Galileo for theEuropean Union, and various other navigation satellite systems. Forexample, the GNSS receiver 22 may be a GPS receiver, which may receiveGPS signals from a constellation of GPS satellites 68. And, in anotherexample, GNSS receiver 22 can be a BDS receiver that receives aplurality of GNSS (or BDS) signals from a constellation of GNSS (or BDS)satellites 68. In either implementation, GNSS receiver 22 can include atleast one processor and memory, including a non-transitory computerreadable memory storing instructions (software) that are accessible bythe processor for carrying out the processing performed by the receiver22. The GNSS receiver 22 can be used to obtain a location of thevehicle, such as a geographic coordinate location.

Body control module (BCM) 24 can be used to control various VSMs of thevehicle, as well as obtain information concerning the VSMs, includingtheir present state or status, as well as sensor information. The BCM 24is shown in the exemplary embodiment of FIG. 1 as being electricallycoupled to communication bus 58. In some embodiments, the BCM 24 may beintegrated with or part of a center stack module (CSM) and/or integratedwith the wireless communications device 30. Or, the BCM 24 may be aseparate device that is connected to other VSMs via bus 58. The BCM 24can include a processor and/or memory, which can be similar to processor36 and memory 38 of the wireless communications device 30, as discussedbelow. The BCM 24 may communicate with the wireless communicationsdevice 30 and/or one or more vehicle system modules, such as the firstsubsystem VSMs 42-46, the second subsystem VSMs 62-66, audio system 56,or other VSMs 28. The BCM 24 may include a processor and memoryaccessible by the processor. Suitable memory may include non-transitorycomputer-readable memory that includes various forms of non-volatile RAMand ROM. Software stored in the memory and executable by the processorenables the BCM to direct one or more vehicle functions or operationsincluding, for example, controlling central locking, air conditioning(or other HVAC functions), power mirrors, controlling the vehicleprimary mover (e.g., engine, primary propulsion system), and/orcontrolling various other vehicle modules. For example, the BCM 24 cansend signals to other VSMs, such as a request to perform a particularoperation or a request for sensor information and, in response, thesensor may then send back the requested information.

Additionally, the BCM 24 may provide vehicle state informationcorresponding to the vehicle state or of certain vehicle components orsubsystems, including the VSMs discussed herein. For example, the BCM 24may provide the wireless communication device 30 with informationindicating whether the vehicle's primary propulsion system is engaged orin an active (or ready) state (or when the ignition is turned on asreceived from an engine control module in an ICE vehicle), diagnosticdata (e.g., DTC(s)), vehicle operation signals, and/or other informationregarding the vehicle. The information can be sent to the wirelesscommunications device 30 (or other central vehicle computer)automatically upon receiving a request from the device/computer,automatically upon certain conditions being met, or periodically (e.g.,at set time intervals). In one embodiment, the vehicle state informationincludes vehicle operation signals and/or diagnostic data (e.g.,DTC(s)), which can be detected by the BCM 24 (or other VSM) and thensent to the backend facility 80 using the wireless communications device30, for example. This vehicle state information can then be stored indatabases 84 and used as a part of the method discussed below, at leastin some embodiments. The vehicle operation signals are communicated overthe communication bus 58 as a part of the normal operation of thevehicle. The BCM 24 (or other VSM) can detect and record the presence ofvehicle operation signals that are being sent over the communication bus58.

Also, in some embodiments, in addition to recording the presence of thevehicle operation signal, other information pertaining to or that is apart of the vehicle operation signal can be recorded, such as one ormore numerical values sent as a part or along with the vehicle operationsignal. The vehicle operation signals data that is recorded at thevehicle can include information pertaining to one or more vehicleoperation signals, such as the presence of the vehicle operation signal,one or more values being conveyed by (or otherwise associated with) thevehicle operation signal, and/or other information pertaining to thevehicle operation signal. The diagnostic data that is recorded at thevehicle can include information pertaining to one or more diagnosticsignals, such as the presence of the diagnostic signal (e.g., thepresence of a DTC), one or more values being conveyed by (or otherwiseassociated with) the diagnostic signal, and/or other informationpertaining to the diagnostic signal. Also, a vehicle location (e.g., asdetermined using the GNSS receiver 22) and/or a time indicator can berecorded along with the vehicle operation signals data and/or thediagnostic data, and/or sent to the backend facility 80.

As mentioned above, in the illustrated embodiment, the vehicle 12includes an internal combustion engine (ICE) and is referred to as anICE vehicle. ICE vehicles may solely use an ICE for propulsion or mayuse a combination of another energy generator or store (such as abattery) and the ICE. In the case of an ICE vehicle, the vehicle caninclude an engine control module (ECM) 26 that controls various aspectsof engine operation such as fuel injection and ignition timing. The ECM26 can be connected to communications bus 58 and may receive operationinstructions from BCM 24 or other vehicle system modules, such as thewireless communications device 30 or VSMs 28. In one scenario, the ECUmay receive a command from the BCM 24 to initiate the ICE. The ECM 26can also be used to obtain sensor information of the vehicle engine.

The engine control module (ECM) 26 may control various aspects of engineoperation such as fuel injection and ignition timing. The ECM 26 isconnected to the communications bus 58 and may receive operationinstructions (or vehicle commands) from the BCM 24 or other vehiclesystem modules. In one scenario, the ECM 26 may receive a command fromthe BCM 24 (or other VSM) to place the vehicle in a primary propulsionon state (from a primary propulsion off state)—i.e., initiate thevehicle ignition or other primary propulsion system (e.g., a batterypowered motor). In at least some embodiments when the vehicle is ahybrid or electric vehicle, a primary propulsion control module can beused instead of (or in addition to) the ECM 26, and this primarypropulsion control module can be used to obtain status informationregarding the primary mover (including electrical motor(s) and batteryinformation). A primary propulsion off state refers to a state in whichthe primary propulsion system of the vehicle is off, such as when theinternal combustion engine is not running or idling, when a vehicle keyis not turned to a START or ON (or accessory) position, or when thepower control system for one or more electric motors of an electricvehicle is powered off or not enabled. A primary propulsion on state isa state that is not a primary propulsion off state.

The vehicle 12 includes various onboard vehicle sensors, includingcameras, parking sensors, lane change and/or blind spot sensors, laneassist sensors, ranging sensors (i.e., sensors used to detect the rangebetween the vehicle and another object, such as through use of radar orlidar), other radars, other lidars, tire-pressure sensors, fluid levelsensors (including a fuel level sensor), brake pad wear sensors, V2Vcommunication unit (which may be integrated into the wirelesscommunications device 30), rain or precipitation sensors (e.g., infraredlight sensor(s) directed toward the windshield (or other window of thevehicle 12) to detect rain or other precipitation based on the amount ofreflected light), and interior or exterior temperature sensors.Generally, the sensors can obtain information pertaining to either theoperating state of the vehicle (the “vehicle operating state”) or theenvironment of the vehicle (the “vehicle environmental state”). Thesensor information can be sent to other VSMs, such as BCM 24 and thevehicle communications device 30, via communications bus 58. Also, insome embodiments, the sensor data can be sent with metadata, which caninclude data identifying the sensor (or type of sensor) that capturedthe sensor data, a timestamp (or other time indicator), and/or otherdata that pertains to the sensor data, but that does not make up thesensor data itself. The “vehicle operating state” refers to a state ofthe vehicle concerning the operation of the vehicle, which can includethe operation of the primary mover (e.g., a vehicle engine, vehiclepropulsion motors). Additionally, the vehicle operating state caninclude information concerning mechanical operations of the vehicle orelectrical states of the vehicle, including information pertaining tovehicle operation signals and/or diagnostic data or signals (e.g.,DTC(s)). The “vehicle environmental state” refers to a vehicle stateconcerning the interior of the cabin and the nearby, exterior areasurrounding the vehicle. The vehicle environmental state includesbehavior of a driver, operator, or passenger, as well as trafficconditions, roadway conditions and features, and statuses of areasnearby the vehicle.

The first subsystem 40 and the second subsystem 60 are each vehiclesubsystems having a plurality of VSMs—in other embodiments, thesubsystem(s) can each have a single VSM. As used herein, a vehiclesubsystem comprises one or more vehicle system modules (VSMs) installedas a part of the vehicle and that operate together to carry out aparticular group of related vehicle functions. The first subsystem 40and the second subsystem 60 can be any of a variety of vehiclesubsystems, including (for example) a fuel delivery subsystem, an airintake subsystem, an electrical subsystem, a braking subsystem, aclimate control subsystem, an entertainment subsystem, etc. The firstsubsystem VSMs 42-46 are each a VSM that is considered as a part of thefirst subsystem 40, and the second subsystem VSMs 62-66 are each a VSMthat is considered as a part of the second subsystem 60.

Wireless communications device 30 is capable of communicating data viashort-range wireless communications (SRWC) and/or via cellular networkcommunications through use of a cellular chipset 34, as depicted in theillustrated embodiment. In the illustrated embodiment, wirelesscommunications device 30 includes an SRWC circuit 32, a cellular chipset34, a processor 36, memory 38, and antennas 33 and 35. In oneembodiment, wireless communications device 30 may be a standalone moduleor, in other embodiments, device 30 may be incorporated or included as apart of one or more other vehicle system modules, such as a center stackmodule (CSM), body control module (BCM) 24, an infotainment module, ahead unit, and/or a gateway module. In some embodiments, the device 30can be implemented as an OEM-installed (embedded) or aftermarket devicethat is installed in the vehicle. In some embodiments, the wirelesscommunications device 30 is a telematics unit (or telematics controlunit) that is capable of carrying out cellular communications using oneor more wireless carrier systems 70. The telematics unit can beintegrated with the GNSS receiver 22 so that, for example, the GNSSreceiver 22 and the wireless communications device (or telematics unit)30 are directly connected to one another as opposed to being connectedvia communications bus 58.

In some embodiments, the wireless communications device 30 can beconfigured to communicate wirelessly according to one or moreshort-range wireless communications (SRWC) such as any of the Wi-Fi™,WiMAX™, Wi-Fi Direct™, other IEEE 802.11 protocols, ZigBee™, Bluetooth™,Bluetooth™ Low Energy (BLE), or near field communication (NFC). As usedherein, Bluetooth™ refers to any of the Bluetooth™ technologies, such asBluetooth Low Energy™ (BLE), Bluetooth™ 4.1, Bluetooth™ 4.2, Bluetooth™5.0, Bluetooth™ 5.1, and other Bluetooth™ technologies that may bedeveloped. As used herein, Wi-Fi™ or Wi-Fi™ technology refers to any ofthe Wi-Fi™ technologies, such as IEEE 802.11b/g/n/ac or any other IEEE802.11 technology. The short-range wireless communication (SRWC) circuit32 enables the wireless communications device 30 to transmit and receiveSRWC signals, such as BLE signals. The SRWC circuit may allow the device30 to connect to another SRWC device. Additionally, in some embodimentsincluding the illustrated embodiment, the wireless communications device30 includes the cellular chipset 34 thereby allowing the device tocommunicate via one or more cellular protocols, such as those used bycellular carrier system 70. In such a case, the wireless communicationsdevice becomes user equipment (UE) usable in carrying out cellularcommunications via cellular carrier system 70.

The wireless communications device 30 may enable the vehicle 12 to be incommunication with one or more remote networks (e.g., one or morenetworks at backend facility 80 or remote computers 78) viapacket-switched data communication. This packet-switched datacommunication may be carried out through use of a non-vehicle wirelessaccess point that is connected to a land network via a router or modem.When used for packet-switched data communication such as TCP/IP, thecommunications device 30 can be configured with a static IP address orcan be set up to automatically receive an assigned IP address fromanother device on the network such as a router or from a network addressserver.

Packet-switched data communications may also be carried out via use of acellular network that may be accessible by the wireless communicationsdevice 30. The device 30 may, via cellular chipset 34, communicate dataover wireless carrier system 70. In such an embodiment, radiotransmissions may be used to establish a communications channel, such asa voice channel and/or a data channel, with wireless carrier system 70so that voice and/or data transmissions can be sent and received overthe channel. Data can be sent either via a data connection, such as viapacket data transmission over a data channel, or via a voice channelusing techniques known in the art. For combined services that involveboth voice communication and data communication, the system can utilizea single call over a voice channel and switch as needed between voiceand data transmission over the voice channel, and this can be done usingtechniques known to those skilled in the art.

Processor 36 can be any type of device capable of processing electronicinstructions including microprocessors, microcontrollers, hostprocessors, controllers, vehicle communication processors, andapplication specific integrated circuits (ASICs). It can be a dedicatedprocessor used only for communications device 30 or can be shared withother vehicle systems. Processor 36 executes various types ofdigitally-stored instructions, such as software or firmware programsstored in memory 38, which enable the device 30 to provide a widevariety of services. The memory 38 may be a temporary powered memory,any non-transitory computer-readable medium, or other type of memory.For example, the memory can be any of a number of different types of RAM(random-access memory, including various types of dynamic RAM (DRAM) andstatic RAM (SRAM)), ROM (read-only memory), solid-state drives (SSDs)(including other solid-state storage such as solid state hybrid drives(SSHDs)), hard disk drives (HDDs), and/or magnetic or optical discdrives. Similar components to those previously described (processor 36and/or memory 38, as well as SRWC circuit 32 and cellular chipset 34)can be included in body control module 24, the ECM 26, the firstsubsystem 40 (e.g., as a part of one or more of the first subsystem VSMs42-46), the second subsystem 60 (e.g., as a part of one or more of thesecond subsystem VSMs 62-66), and/or various other VSMs that typicallyinclude such processing/storing capabilities. The wirelesscommunications device 30 is connected to the bus 58, and can receiveDTC(s) (or other diagnostic data) and/or vehicle operation signals thatare sent over the communications bus 58. The vehicle can send this data(or other data derived from or based on this data) to other devices ornetworks, including the backend facility 80.

Vehicle electronics 20 also includes a number of vehicle-user interfacesthat provide vehicle occupants with a means of providing and/orreceiving information, including visual display 50, pushbutton(s) 52,microphone 54, and audio system 56. As used herein, the term“vehicle-user interface” broadly includes any suitable form ofelectronic device, including both hardware and software components,which is located on the vehicle and enables a vehicle user tocommunicate with or through a component of the vehicle. Thepushbutton(s) 52 allow manual user input into the communications device30 to provide other data, response, or control input. Audio system 56provides audio output to a vehicle occupant and can be a dedicated,stand-alone system or part of the primary vehicle audio system.According to the particular embodiment shown here, audio system 56 isoperatively coupled to both the communication bus 58 and anentertainment bus (not shown), and can provide AM, FM and satelliteradio, CD, DVD and other multimedia functionality. This functionalitycan be provided in conjunction with or independent of an infotainmentmodule. Microphone 54 provides audio input to the wirelesscommunications device 30 to enable the driver or other occupant toprovide voice commands and/or carry out hands-free calling via thewireless carrier system 70. For this purpose, it can be connected to anon-board automated voice processing unit utilizing human-machineinterface (HMI) technology known in the art. Visual display or touchscreen 50 is preferably a graphics display and can be used to provide amultitude of input and output functions. Display 50 can be a touchscreen on the instrument panel, a heads-up display reflected off of thewindshield, or a projector that can project graphics for viewing by avehicle occupant. Various other vehicle-user interfaces can also beutilized, as the interfaces of FIG. 1 are only an example of oneparticular implementation.

With reference to FIG. 2, there is shown an embodiment of a method 200of performing fault diagnosis and analysis for one or more vehicles. Themethod 200 can be carried out by the backend facility 80 using one ormore servers 82 and, in at least some embodiments, can be carried outusing a plurality of servers. In another embodiment, the method 200 canbe carried out at one or more remote computers 78. In other embodiments,the method 200 can be carried out by a combination of the servers 82 ofthe backend facility 80 and the one or more remote computers 78. In oneembodiment, the steps 210-240 of the method 200 are carried out by theDFMEA augmentation application, and the step 250 of the method 200 iscarried out by the vehicle fault diagnosis and analysis application.Although the DFMEA augmentation application and the vehicle faultdiagnosis and analysis application are each referred to or discussed asa single application in the following description, these applicationscan each be comprised of one or more computer applications that arecarried out on one or more computers, any one or more of which can be apart of the backend facility 80 (or other backend facility) and/or theremote computers 78. The steps of the method 200 can be carried outaccording to any technically feasible order, as appreciated by thoseskilled in the art.

The method 200 begins with step 210, wherein design failure mode andeffect analysis (DFMEA) data is obtained. The DFMEA data is generated asa part of the design, manufacturing, and/or initial testing of avehicle, one or more subsystems of the vehicle, and/or one or more VSMsor other components of the vehicle. The DFMEA data can be embodied incomputer-readable data and/or in one or more DFMEA documents. The DFMEAdata specifies a plurality of failure modes and can include descriptionsof each of the plurality of failure modes. Also, in some embodiments,the DFMEA data can include symptom data for each of the failure modes.The symptom data is data that describes or indicates one or moresymptoms of the vehicle as a result of (or indicative of) a particularfailure mode. The DFMEA data can also include a part identifier for eachfailure mode. The part identifier is information that identifies a partor an interface of the vehicle that is deemed to be associated with theparticular failure mode, such as a part or an interface that isconsidered as failing as a part of the failure mode.

In one embodiment, the DFMEA data is DFMEA information for a particularsubsystem of the vehicle. Additionally or alternatively, the DFMEA datais DFMEA information for a plurality of subsystems of the vehicle. Forexample, a first DFMEA document (or data) for the first subsystem 40 canbe generated, a second DFMEA document (or data) for the second subsystem60 can be generated, and then the first DFMEA document and the secondDFMEA document (or data) can be combined with one another to obtain amulti-subsystem DFMEA document (or data). Also, the DFMEA data caninclude the first DFMEA data (e.g., the first DFMEA document) and/or thesecond DFMEA data (e.g., the second DFMEA document). In one embodiment,the DFMEA data can be inputted by a technical specialist into a computersystem, such as a computer connected to or that is a part of the backendfacility 80. The DFMEA data can be inputted into the computer system ata time of manufacturing the vehicle, or the portion of the vehicle towhich it relates (e.g., the first subsystem, the second subsystem).

In some embodiments, as a part of obtaining the DFMEA data, the DFMEAdata can be recalled from a database, such as from the DFMEA database ofthe databases 84, or from other memory, such as the memory of one ormore of the remote computers 78 or servers 82. This obtaining step canalso include providing the DFMEA data to a first technical specialist,which can include presenting the DFMEA data to one or more technicalspecialists using a computer, such as the remote computer 78, servers82, or other remote computer. As mentioned above, the DFMEA data can beembodied in one or more DFMEA documents. These DFMEA documents can bepresented or otherwise provided to the one or more technical specialistsusing a computer application that is suited for or capable ofinterpreting or reading the DFMEA document(s), such as, for example,Microsoft Excel™ in the case that the DFMEA document(s) are CSV files,Excel™ files (e.g., “xls”, “xlsx”), or other file readable by MicrosoftExcel™. The method 200 then continues to step 220.

In steps 220 and 230, diagnostic association data and vehicle operationsignals association data is received at one or more computers, such asat one or more remote computers (e.g., remote computer(s) 78). Thisreceived diagnostic association data indicates diagnostic data orindicators (e.g., DTC(s)) to be associated with the DFMEA data that wasobtained in step 210. This received vehicle operation signalsassociation data indicates vehicle operation signals data to beassociated with the DFMEA data that was obtained in step 210. Thesesteps can be carried out at different locations, such as at a firstremote computer (for step 220) and a second remote computer (for step230). Although step 230 is illustrated and discussed below as beingcarried out after step 220, in other embodiments, step 220 and step 230can be carried out at the same time, or step 230 may be carried outprior to step 220. After steps 220 and 230 are carried out, in step 240,augmented DFMEA data (e.g., an augmented DFMEA document) is generatedbased on (or as a result of receiving) the received diagnosticassociation data and vehicle operation signals association data.

In step 220, diagnostic association data is received and, in manyembodiments, DTC data (an example of diagnostic data) is received. Thediagnostic association data includes one or more identifiers orindicators that identify or indicate one or more diagnostic signals(e.g., DTC(s)) (or other diagnostic data) that each are associated with(or are to be associated with) a failure mode of the plurality offailure modes specified in the DFMEA data. It should be appreciatedthat, in some scenarios, there may not be diagnostic data (or a DTC)associated with one or more of the failure modes of the DFMEA data and,in such a case, no diagnostic association data is received for thatfailure mode. The failure modes that are associated with diagnostic databased on the diagnostic association data can be referred to as a firstset of failure modes, which can include one or more failure modes of theplurality of failure modes in the DFMEA data. The DTC(s) can be inputinto a computer by a first technical specialist, such as a hardwaretechnical specialist. The first technical specialist can be a specialistwith respect to a particular subsystem, VSM, or other portion of thevehicle to which the DFMEA data pertains. In at least some embodiments,the DFMEA data is presented to the first technical specialist at a firstcomputer (e.g., a first one of the remote computers 78), and the firsttechnical specialist then can view the DFMEA data and provide diagnosticassociation data (e.g., DTC(s), a selection or indication of one or moreDTCs or other diagnostic data) that is associated with each of thefailure modes presented as a part of the DFMEA data. For example, in oneembodiment, the first technical specialist can be provided with a DFMEAdocument that describes a plurality of failure modes with each failuremode being presented within its own row of a table or spreadsheet (e.g.,an Excel™ spreadsheet). In such an example, the first technicalspecialist can then insert or otherwise provide diagnostic associationdata (e.g., DTC(s), other diagnostic indicators) in a new column and canfill in each cell of this new column based on the failure mode in therow that contains the cell. In some embodiments, the DFMEA augmentationapplication can be used for this step and can include a graphical userinterface (GUI) that facilitates entry or input of the diagnosticassociation data. The first technical specialist can provide thediagnostic association data by typing on a keyboard that iscommunicatively coupled to the first computer. Other input means can beused as well, such as by selecting a DTC from a list of DTCs using amouse. The method 200 continues to step 230.

In step 230, vehicle operation signals association data is received. Thevehicle operation signals association data is one or more identifiers orindicators that identify or indicate one or more vehicle operationsignals (or other vehicle operation signals data) that each areassociated with (or are to be associated with) a failure mode of theplurality of failure modes specified in the DFMEA data. It should beappreciated that, in some scenarios, there may not be a vehicleoperation signal (or other vehicle operation signals data) associatedwith one or more of the failure modes of the DFMEA data and, in such acase, no vehicle operation signals association data is received for thatfailure mode. The failure modes that are associated with vehicleoperation signals data based on the vehicle operation signalsassociation data can be referred to as a second set of failure modes,which can include one or more failure modes of the plurality of failuremodes in the DFMEA data. The vehicle operation signals association datacan be input into a computer by a second technical specialist, such as asignals or controls technical specialist. In one embodiment, the secondtechnical specialist can be the same individual as the first technicalspecialist; however, in other embodiments, the first technicalspecialist and the second technical specialist are different technicalspecialists. The second technical specialist can be a specialist withrespect to a particular subsystem, VSM, or other portion of the vehicleto which the DFMEA data describes or is otherwise associated with. In atleast some embodiments, the DFMEA data is presented to the secondtechnical specialist at a second computer (e.g., a second one of theremote computers 78), and the second technical specialist then can viewthe DFMEA data and provide vehicle operation signals association datafor each of the failure modes presented as a part of the DFMEA data. Forexample, in one embodiment, the second technical specialist can beprovided with a DFMEA document that describes a plurality of failuremodes with each failure mode being presented within its own row. ThisDFMEA document can be the same DFMEA document that was provided to thefirst technical specialist in step 220. In such an example, the secondtechnical specialist can then insert or otherwise provide vehicleoperations signal association data in a new column and can fill in eachcell of this new column based on the failure mode in the row thatcontains the cell. In some embodiments, the DFMEA augmentationapplication can be used for this step and can include a GUI thatfacilitates entry or input of the vehicle operation signals associationdata. The second technical specialist can provide the vehicle operationsignals association data by typing on a keyboard that is communicativelycoupled to the second computer. Other input means can be used as well,such as by selecting a vehicle operation signal from a list of vehicleoperation signals using a mouse. The method 200 continues to step 240.

In step 240, augmented DFMEA data is generated based on the diagnosticassociation data and the vehicle operation signals association data. Inat least some embodiments, the augmented DFMEA data provides a causalrelationship between diagnostic data (e.g., DTC(s)) and one or morefailure modes of the DFMEA data, and this causal relationship can beindicated by (or based on) the diagnostic association data. Also, in atleast some embodiments, the augmented DFMEA data provides a causalrelationship between vehicle operation signals data (e.g., informationconcerning one or more electronic signals used as a part of operation ofthe vehicle) and one or more failure modes of the DFMEA data, and thiscausal relationship can be indicated by (or based on) the vehicleoperation signals association data. The augmented DFMEA data can includethe diagnostic association data and the vehicle operation signalsassociation data, or other information that associates certain DTC(s)(or other diagnostic data) and certain vehicle operation signals (orother vehicle operation signals data) with each of the failure modes,for example. However, as mentioned above, some failure modes may not beassociated with any particular diagnostic data and/or vehicle operationsignals data and, in such cases, the DFMEA data for these failure modesmay not be augmented with the diagnostic association data, the vehicleoperation signals association data, and/or data derived therefrom.

In one embodiment, the augmented DFMEA data includes one or moreaugmented DFMEA documents. The augmented DFMEA document(s) can be of aparticular format or file type. In some embodiments, the augmented DFMEAdocument(s) are a modified version of one or more DFMEA documents withthe modifications being that the diagnostic association data and thevehicle operation signals association data is included. For example, inan embodiment where the DFMEA document for a first subsystem is aspreadsheet having rows for each failure mode, an augmented DFMEAdocument can be generated by inserting new columns into the DFMEAdocument with a first column being for the diagnostic association dataand a second column being for the vehicle operation signals associationdata. The augmented DFMEA data can be stored at a database, such as anyone or more of those databases 84 (e.g., in the DFMEA database). Themethod 200 continues to step 250.

In step 250, fault diagnosis and analysis is carried out using theaugmented DFMEA data. The fault diagnosis and analysis includes faultdiagnosis for one or more vehicles, fault analysis for one or morevehicles, or both. The fault diagnosis can include providing theaugmented DFMEA data to a vehicle service facility or technician (orother individual) that is attempting to diagnose problems of one or morevehicles. In another embodiment, the augmented DFMEA data can be used toautomatically (or programmatically) monitor and/or diagnose one or morevehicles for various problems. In such embodiments, for example, theaugmented DFMEA data can be used by the backend facility 80 to analyzevehicle state information received from one or more vehicles. As anexample, the backend facility 80 can identify (based on the vehiclestate information or other information received from the vehicle) one ormore DTCs and/or vehicle operation signals that were detected at thevehicle. The backend facility 80 can then parse or query the augmentedDFMEA data to identify a failure mode that is associated with these oneor more DTCs and/or vehicle operation signals. A message can then begenerated at the backend facility 80 and sent to the vehicle or otherclient device, such as a smartphone or other personal mobile device. Themessage can indicate the identified failure mode and can be presented toa vehicle user or service technician using one or more vehicle-userinterfaces, such as display 50.

Additionally or alternatively, fault analysis can be carried out usingthe augmented DFMEA data. The fault analysis can include analyzing theaugmented DFMEA data to identify causal relationships between certainfailure modes (and/or their symptoms), DTC(s), and vehicle operationsignal(s), as well as between the VSM(s) and/or subsystem(s) related tothe failure modes, DTC(s) (or other diagnostic data), and vehicleoperation signal(s) (or other vehicle operation signals data). In oneembodiment, a machine learning (ML) or artificial intelligence (AI)technique can be applied to historical diagnostic data and/or historicalvehicle operation signals data based on (or using) the augmented DFMEAdata. Also, in at least some embodiments, the historical diagnostic dataand the historical vehicle operation signals data can be used to trainthe AI classifier so that when real-time data is presented to the AIcomputer application, the AI classifier can help, assist, or otherwisebe used to identify the failure mode. In such an embodiment, an AIclassifier can be developed and/or designed based on the causalrelationships identified in or determined based on the augmented DFMEAdata. The AI classifier can then be used by an AI computer applicationor network to diagnose problems of one or more vehicles based onhistorical diagnostic data and/or historical vehicle operation signalsdata stored in databases 84. The identification of the causalrelationships and the development of the AI classifier is an example offault analysis, and the diagnosis using the AI computer application isan example of fault diagnosis. The AI computer application can also beoperated using real-time data from the one or more vehicles—that is,diagnostic data and/or vehicle operation signals data can be detectedand sent to the backend facility 80 in real-time and, then, the backendfacility 80 can execute the AI computer application using this real-timediagnostic data and/or vehicle operation signals data. The real-timediagnostic data and the real-time vehicle operation signals data isconsidered a type of historical diagnostic data and historical vehicleoperation signals data, respectively. As used herein, diagnostic datathat is detected or otherwise observed at a particular vehicle as a partof the particular vehicle's operation is referred to as observeddiagnostic data, and vehicle operation signals data that is detected orotherwise observed at a particular vehicle as a part of the particularvehicle's operation is referred to as observed vehicle operation signalsdata. This observed diagnostic data and observed vehicle operationsignals data can be stored as historical diagnostic data and historicalvehicle operation signals data in databases. However, it should beappreciated that, in at least some embodiments, not all observeddiagnostic data and observed vehicle operation signals data is stored ashistorical diagnostic data and historical vehicle operation signalsdata.

As another example of fault analysis, the augmented DFMEA data can beanalyzed or inspected to determine whether each failure mode isisolatable or distinguishable from the other failure modes. A firstfailure mode is isolatable or distinguishable from a second failure modewhen the vehicle operation signals and the DTC(s) (or other diagnosticdata) associated with the first failure mode are different than thevehicle operation signals and the DTC(s) (or other diagnostic data)associated with the second failure mode. When two failure modes includethe same diagnostic association data (or are associated with the sameDTC(s) or other diagnostic data) and the same vehicle operation signalsassociation data (or are associated with the same vehicle operationsignals data), then a single failure mode cannot be determined (at leastfrom this information alone) and, thus, such failure modes areconsidered not isolatable. As mentioned above, the vehicle operationsignals data can indicate a presence of a particular signal and, in atleast some embodiments, can also indicate a value or other informationthat is conveyed by (or otherwise associated with) the vehicle operationsignals data. Thus, in at least some embodiments, when comparing thevehicle operation signals association data, the comparison can includecomparing both the presence of a particular vehicle operation signal aswell as the values or other information that is conveyed by (orotherwise associated with) the vehicle operation signals data. Thus, byanalyzing the augmented DFMEA data, two or more failure modes can beidentified that are not isolatable. These identified failure modes canthen be provided to a technical specialist or other individual who canthen use this information as design feedback and/or to improve thevehicle or vehicle models associated with these non-isolatable failuremodes.

In some embodiments, the steps 210-240 can be carried out by a supplierof a vehicle OEM of the one or more vehicles. In such embodiments, forexample, the DFMEA augmentation application can be provided to thesupplier, which can then use this application to generate the augmentedDFMEA data. The supplier can then provide the augmented DFMEA data tothe OEM so that it can be used for fault diagnosis and analysis. In somescenarios, the DFMEA data of a particular component, VSM, or subsystemmay be considered confidential by the manufacturer or designer (e.g., asupplier) and, in such cases, the manufacturer or designer may not wantto provide this DFMEA data to another entity (e.g., an OEM). Thus, insuch a scenario, for example, it may be desirable for the OEM to providethe DFMEA augmentation application to the supplier and then the suppliercan use the DFMEA augmentation application to generate the augmentedDFMEA data. The supplier can then identify causal relationships betweenone or more failure modes, subsystems, and/or VSMs based on thediagnostic association data and/or the vehicle operation signals data,and these identified causal relationships can be represented by causalrelationship data. This causal relationship data can then be provided tothe OEM while still maintaining secrecy or confidentiality for portionsof the augmented DFMEA data, such as the DFMEA data that was originallydeveloped and deemed confidential.

In one embodiment, a first supplier can generate first augmented DFMEAdata for a first subsystem used by a vehicle that is (or includes VSMsthat are) developed by the first supplier, and a second supplier cangenerate second augmented DFMEA data for a second subsystem used by thevehicle that is (or includes VSMs that are) developed by the secondsupplier. The first augmented DFMEA data and the second augmented DFMEAdata can then be analyzed to develop a dependency model, which canprovide for identifying causal relationships between the first andsecond subsystems.

With reference to FIG. 3, there is shown another embodiment of a method300 of performing fault diagnosis and analysis for one or more vehicles.The method 300 includes steps that are similar to those of the method200 (FIG. 2) discussed above, and such discussion is incorporated hereinto the extent it does not conflict with the below discussion. Also, anyother discussion of the method 200 is incorporated herein with respectto the method 300 to the extent it does not conflict with the belowdiscussion. The steps of the method 300 can be carried out according toany technically feasible order, as appreciated by those skilled in theart.

The method 300 is described below with respect to an exemplary scenarioin which the first subsystem 40 is an air intake subsystem of a vehicleand the second subsystem 60 is a fuel delivery subsystem of a vehicle.The method 300 begins with step 302, wherein design failure mode andeffect analysis (DFMEA) data is obtained. The DFMEA data is indicated at302 in FIG. 3 and, in this example, includes a first DFMEA document 304and a second DFMEA document 306. The first DFMEA document 304 isindicative of a first failure mode of the first subsystem and, in thisexample, the first failure mode of the first subsystem is an inductionsystem leak in which the air is not suitably provided to the engine. Thesecond DFMEA document 306 is indicative of a first failure mode of thesecond subsystem and, in this example, the first failure mode of thesecond subsystem is indicative of an injector being choked or plugged inwhich fuel is not suitably delivered to the combustion chamber of theengine. In at least some embodiments, the first DFMEA document 304 doesnot include DFMEA data concerning the second subsystem, and/or thesecond DFMEA document 306 does not include DFMEA data concerning thefirst subsystem. Also, in one embodiment, the first DFMEA document 304includes DFMEA data that only concerns the first subsystem (and notother subsystems), and the second DFMEA document 306 includes DFMEA datathat only concerns the second subsystem (and not other subsystems).

In step 312, diagnostic association data for a first set of theplurality of failure modes is received and, in many embodiments, DTCdata (an example of diagnostic data) is received. As shown in FIG. 3,this diagnostic association data is received from a first technicalspecialist 310. This diagnostic association data concerns at least oneof the first failure mode of the first subsystem and/or the firstfailure mode of the second subsystem. In step 322, vehicle operationsignals association data is received for a second set of the pluralityof failure modes. As shown in FIG. 3, this vehicle operation signalsassociation data is received from a second technical specialist 320.This vehicle operation signals association data concerns at least one ofthe first failure mode of the first subsystem and/or the first failuremode of the second subsystem. The first technical specialist can be ahardware specialist or other specialist that has knowledge concerningthe diagnostics of the vehicle, including the first and/or secondsubsystems. The second technical specialist can be a software or signalsspecialist (or other specialist) that has knowledge concerning thevehicle operation signals of the vehicle, including those of used by thefirst and/or second subsystems. In one embodiment, a first technicalspecialist can provide diagnostic association data for the firstsubsystem, a second technical specialist can provide vehicle operationsignals association data for the first subsystem, a third technicalspecialist can provide diagnostic association data for the secondsubsystem, and a fourth technical specialist can provide vehicleoperation signals association data for the second subsystem. Thediagnostic association data and the vehicle operation signalsassociation data can be used to generate augmented DFMEA data 330.

In one embodiment, the augmented DFMEA data 330 includes a firstaugmented

DFMEA document 332 that includes augmented DFMEA data for the firstsubsystem, and a second augmented DFMEA document 334 that includesaugmented DFMEA data for the second subsystem. According to someembodiments, the first augmented DFMEA document (or data) indicates thecausal relationship between the diagnostic data and a third set offailure modes, and/or the first augmented DFMEA document indicates thecausal relationship between the vehicle operation signals data and afourth set of failure modes. The third set of failure modes are thosefailure modes that are a part of the first set of failure modes and thefirst subsystem failure modes (i.e., the failure modes specified in theDFMEA data for the first subsystem), and the fourth set of failure modesare those failure modes that are a part of the second set of failuremodes and the first subsystem failure modes. Also, according to someembodiments, the second augmented DFMEA document (or data) indicates thecausal relationship between the diagnostic data and a fifth set offailure modes, and/or the second augmented DFMEA document indicates thecausal relationship between the vehicle operation signals data and asixth set of failure modes. The fifth set of failure modes are thosefailure modes that are a part of the first set of failure modes and thesecond subsystem failure modes (i.e., the failure modes specified in theDFMEA data for the second subsystem), and the sixth set of failure modesare those failure modes that are a part of the second set of failuremodes and the second subsystem failure modes. Any of the sets of failuremodes (e.g., the first set, the second set, the third set, the fourthset, the fifth set, the sixth set) can include one or more failure modesor a plurality of failure modes. The method 300 continues to step 340.

In step 340, a dependency model can be generated based on the augmentedDFMEA data that captures causal relationship(s) between the failuremodes of the various subsystems, and which can be identified based onthe diagnostic association data and/or vehicle operation signalsassociation data. The dependency model 350 of FIG. 3 thus includesinterrelationships between failure modes 352 of the first subsystem andthe second subsystem, and the diagnostic association data 354 and thevehicle operations association data 356. For example, the dependencymodel 350 can include rows for each of the failure modes 352 (includingthe first subsystem failure modes and the second subsystem failuremodes), a first set of columns for the diagnostic association data 354,and a second set of columns for the vehicle operations association data356. In each cell, which corresponds to either a diagnostic data/failuremode pair or a vehicle operation signals data/failure mode pair, anindicator (e.g., an “X”, a numerical value) can be used to indicatewhether there is a causal relationship between the diagnostic data andthe failure mode, or between the vehicle operation signals data and thefailure mode. In one embodiment, the indicator can be binary (e.g., an“X” to indicate a relationship exists, no entry to indicate norelationship exists), or can include a value (e.g., a numerical value)or other indicator (e.g., a designated level) that indicates the degreeor strength of the relationship between the diagnostic data and thefailure mode, or between the vehicle operation signals data and thefailure mode. In some embodiments, the strength of the correlation andthe value (or other data being conveyed by the signal) can be used toindicate a particular failure. Moreover, in some embodiments, the value(or degree of other data being conveyed by the signal) can be used toindicate the probability or confidence that a particular failure mode ispresent.

This step 340 can include extracting information concerning the firstsubsystem from the first augmented DFMEA document (or data) andinformation concerning the second subsystem from the second augmentedDFMEA document (or data). In one embodiment, the first augmented DFMEAdocument (or data) may indicate that the first failure mode of the firstsubsystem can be associated with the DTCs P0101, P0106, P0171, andP0174. The second augmented DFMEA document (or data) may indicate thatthe first failure mode of the second subsystem can be associated withthe DTCs P0171 and P0174. Thus, by combining the first augmented DFMEAdata with the second augmented DFMEA data, the dependency model canindicate that, when the DTCs P0171 and P0174 are detected at a vehicle,the air induction system should be inspected by, for example,determining whether the DTCs P0101 and/or P0106 are present, and/orwhether vehicle operations data (or signals) pertaining to the firstfailure mode of the first subsystem are present. This dependency modelcan thus be used to evaluate and/or analyze diagnostic conditions and/orvehicle operations signals with respect to multiple subsystems whileconsidering the interrelationships of operation (or failure modes) amongthese multiple subsystems.

In step 360, an artificial intelligence (AI) classifier is developedand/or designed based on the dependency model generated in step 340. TheAI classifier can be developed and/or designed based on the causalrelationships identified in the dependency model. Various techniquesknown to those skilled in the art concerning the design, development,and/or generation of AI classifiers or other information used as a partof an AI or machine learning (ML) technique or network can be used. Themethod 300 continues to step 370.

In step 370, fault diagnosis and analysis is carried out using thedependency model. As mentioned in step 250 of the method 200 above, manydifferent types of fault diagnosis and analysis can be carried out. Inan exemplary embodiment, the AI classifier obtained in step 360 can beused by an AI computer application or network to diagnose problems ofone or more vehicles based on historical diagnostic data and/orhistorical vehicle operation signals data stored in databases 84. The AIcomputer application, which can be executed at the remote computers 78and/or servers 82, can also be operated using real-time data from theone or more vehicles—that is, for example, diagnostic data and/orvehicle operation signals data can be detected and sent to the backendfacility 80 in real-time and, then, the backend facility 80 can executethe AI computer application using this real-time diagnostic data and/orvehicle operation signals data. The method 300 then ends.

In one embodiment, the method 200, the method 300, and/or step(s) orparts thereof can be implemented in one or more computer programs (or“applications”, or “scripts”) embodied in one or more computer readablemediums and including instructions usable (e.g., executable) by one ormore processors of the one or more computers of one or more systems. Thecomputer program(s) may include one or more software programs comprisedof program instructions in source code, object code, executable code, orother formats. In one embodiment, any one or more of the computerprogram(s) can include one or more firmware programs and/or hardwaredescription language (HDL) files. Furthermore, the computer program(s)can each be associated with any program related data and, in someembodiments, the computer program(s) can be packaged with the programrelated data. The program related data may include data structures,look-up tables, configuration files, certificates, or other relevantdata represented in any other suitable format. The program instructionsmay include program modules, routines, programs, functions, procedures,methods, objects, components, and/or the like. The computer program(s)can be executed on one or more computers, such as on multiple computersthat are in communication with one another.

The computer program(s), including the DFMEA augmentation applicationand the vehicle fault diagnosis and/or analysis application, can beembodied on computer readable media (e.g., memory of the vehicle 12(e.g., memory 38, other vehicle memory, memory of the remote computers78, memory of the backend facility 80, a combination thereof), which canbe non-transitory and can include one or more storage devices, articlesof manufacture, or the like. Exemplary computer readable media includecomputer system memory, e.g. RAM (random access memory), ROM (read onlymemory); semiconductor memory, e.g. EPROM (erasable, programmable ROM),EEPROM (electrically erasable, programmable ROM), flash memory; magneticor optical disks or tapes; and/or the like. The computer readable mediummay also include computer to computer connections, for example, whendata is transferred or provided over a network or another communicationsconnection (either wired, wireless, or a combination thereof). Anycombination(s) of the above examples is also included within the scopeof the computer-readable media. It is therefore to be understood thatthe method can be at least partially performed by any electronicarticles and/or devices capable of carrying out instructionscorresponding to one or more steps of the disclosed method.

It is to be understood that the foregoing is a description of one ormore embodiments of the invention. The invention is not limited to theparticular embodiment(s) disclosed herein, but rather is defined solelyby the claims below. Furthermore, the statements contained in theforegoing description relate to particular embodiments and are not to beconstrued as limitations on the scope of the invention or on thedefinition of terms used in the claims, except where a term or phrase isexpressly defined above. Various other embodiments and various changesand modifications to the disclosed embodiment(s) will become apparent tothose skilled in the art. All such other embodiments, changes, andmodifications are intended to come within the scope of the appendedclaims.

As used in this specification and claims, the terms “e.g.,” “forexample,” “for instance,” “such as,” and “like,” and the verbs“comprising,” “having,” “including,” and their other verb forms, whenused in conjunction with a listing of one or more components or otheritems, are each to be construed as open-ended, meaning that the listingis not to be considered as excluding other, additional components oritems. Other terms are to be construed using their broadest reasonablemeaning unless they are used in a context that requires a differentinterpretation. In addition, the term “and/or” is to be construed as aninclusive OR. Therefore, for example, the phrase “A, B, and/or C” is tobe interpreted as covering any one or more of the following: “A”; “B”;“C”; “A and B”; “A and C”; “B and C”; and “A, B, and C.”

What is claimed is:
 1. A method of performing fault diagnosis and analysis for one or more vehicles, comprising the steps of: obtaining design failure mode and effect analysis (DFMEA) data, wherein the DFMEA data specifies a plurality of failure modes; receiving diagnostic association data, wherein the diagnostic association data specifies, for each of a first set of the plurality of failure modes, diagnostic data that is to be associated with the failure mode; receiving vehicle operation signals association data, wherein the vehicle operation signals association data specifies, for each of a second set of the plurality of failure modes, vehicle operation signals data that is to be associated with the failure mode; generating augmented DFMEA data that indicates a causal relationship between the diagnostic data and the first set of failure modes, and that indicates a causal relationship between the vehicle operation signals data and the second set of failure modes, wherein the augmented DFMEA data is generated based on the DFMEA data, the diagnostic association data, and the vehicle operation signals association data; and performing fault diagnosis and analysis for the one or more vehicles using the augmented DFMEA data.
 2. The method of claim 1, wherein the DFMEA data includes or is based on a first DFMEA document that is generated as a part of designing, developing, manufacturing, and/or testing a first subsystem of the one or more vehicles, wherein the DFMEA data includes or is based on a second DFMEA document that is generated as a part of designing, developing, manufacturing, and/or testing a second subsystem of the one or more vehicles.
 3. The method of claim 2, wherein the plurality of failure modes includes a plurality of first subsystem failure modes and a plurality of second subsystem failure modes, wherein the plurality of first subsystem failure modes specifies failure modes pertaining to the first subsystem, and wherein the plurality of second subsystem failure modes specifies failure modes pertaining to the second subsystem.
 4. The method of claim 3, wherein the augmented DFMEA data includes a first augmented DFMEA document and a second augmented DFMEA document, wherein the first augmented DFMEA document indicates the causal relationship between the diagnostic data and a third set of failure modes, wherein the third set of failure modes are those failure modes that are a part of the first set of failure modes and the first subsystem failure modes, wherein the first augmented DFMEA document indicates the causal relationship between the vehicle operation signals data and a fourth set of failure modes, and wherein the fourth set of failure modes are those failure modes that are a part of the second set of failure modes and the first subsystem failure modes.
 5. The method of claim 4, wherein the second augmented DFMEA document indicates the causal relationship between the diagnostic data and a fifth set of failure modes, wherein the fifth set of failure modes are those failure modes that are a part of the first set of failure modes and the second subsystem failure modes, wherein the second augmented DFMEA document indicates the causal relationship between the vehicle operation signals data and a sixth set of failure modes, and wherein the sixth set of failure modes are those failure modes that are a part of the second set of failure modes and the second subsystem failure modes.
 6. The method of claim 5, further comprising the step of generating a dependency model based on the augmented DFMEA data, wherein the dependency model captures causal relationship(s) between the first subsystem failure modes and the second subsystem failure modes, and wherein the causal relationship(s) are identified based on the first augmented DFMEA document and the second augmented DFMEA document.
 7. The method of claim 1, wherein the diagnostics association data is received from a first technical specialist at a first computer, and wherein the vehicle operation signals association data is received from a second technical specialist at a second computer.
 8. The method of claim 1, wherein the fault diagnosis and analysis includes generating an artificial intelligence (AI) classifier based on the augmented DFMEA data.
 9. The method of claim 8, wherein the fault diagnosis and analysis includes executing an AI computer application to diagnose the one or more vehicles based on observed diagnostic data and/or observed vehicle operation signals data pertaining to the one or more vehicles, and wherein the AI computer application is configured to use the AI classifier to diagnose the one or more vehicles.
 10. The method of claim 9, further comprising the step of sending a message to at least one of the one or more vehicles, wherein the message indicates a particular failure mode of the plurality of failure modes that is identified based on the diagnosis performed using the AI computer application.
 11. The method of claim 1, wherein the fault diagnosis and analysis includes determining whether each of the plurality of failure modes are isolatable from one another.
 12. A method of performing fault diagnosis and analysis for one or more vehicles, comprising the steps of: obtaining design failure mode and effect analysis (DFMEA) data, wherein the DFMEA data specifies a plurality of failure modes including first subsystem failure modes and second subsystem failure modes; receiving diagnostic association data, wherein the diagnostic association data specifies, for each of a first set of the plurality of failure modes, one or more diagnostic trouble code(s) (DTC(s)) that are to be associated with the failure mode; receiving vehicle operation signals association data, wherein the vehicle operation signals association data specifies, for each of a second set of the plurality of failure modes, vehicle operation signals data that is to be associated with the failure mode; generating augmented DFMEA data that indicates the DTC(s) that are observable at the one or more vehicles when the one or more vehicles are experiencing any failure mode(s) of the first set of failure modes, and that indicates the vehicle operation signals data that is observable at the one or more vehicles when the one or more vehicles are experiencing any failure mode(s) of the second set of failure modes, wherein the augmented DFMEA data is generated based on the DFMEA data, the diagnostic association data, and the vehicle operation signals association data; generating a dependency model based on the augmented DFMEA data, wherein the dependency model indicates causal relationships between the first subsystem failure modes and the second subsystem failure modes; and performing fault diagnosis and analysis for the one or more vehicles using the augmented DFMEA data.
 13. The method of claim 12, wherein the fault diagnosis and analysis includes: obtaining observed diagnostic data and observed vehicle operation signals data pertaining to at least one of the one or more vehicles, and identifying a failure mode of the at least one vehicle by comparing the observed diagnostic data to diagnostic data as indicated in the dependency model and by comparing the observed vehicle operation signals data to vehicle operation signals data as indicated in the dependency model.
 14. The method of claim 12, wherein a first portion of the diagnostics association data is received from a first technical specialist at a first computer and a second portion of the diagnostics association data is received from a second technical specialist at a second computer.
 15. The method of claim 14, wherein a first portion of the vehicle operation signals association data is received from a third technical specialist at a third computer and a second portion of the vehicle operation signals association data is received from a fourth technical specialist at a fourth computer.
 16. The method of claim 12, wherein the method is carried out by one or more computers that are located remotely from the one or more vehicles.
 17. A vehicle fault diagnosis and analysis system, comprising: one or more computers each having a processor; and memory storing computer instructions that are executable by the one or more computers, wherein the memory is communicatively coupled to the one or more computers; wherein, when the computer instructions are executed by the one or more computers, the vehicle fault diagnosis and analysis system: obtains augmented design failure mode and effect analysis (DFMEA) data that indicates diagnostic data that is observable at one or more vehicles when the one or more vehicles are experiencing any failure mode(s) of a first set of failure modes, and that indicates vehicle operation signals data that is observable at the one or more vehicles when the one or more vehicles are experiencing any failure mode(s) of a second set of failure modes, wherein the augmented DFMEA data is generated based on DFMEA data, diagnostic association data, and vehicle operation signals association data; and performs fault diagnosis and analysis for the one or more vehicles using the augmented DFMEA data.
 18. The vehicle fault diagnosis and analysis system of claim 17, wherein the augmented DFMEA data is generated by a DFMEA augmentation application that is executable by one or more remote computers, wherein, when the DFMEA augmentation application is executed, the one or more remote computers: obtain the DFMEA data, wherein the DFMEA data specifies a plurality of failure modes including the first set of failure modes and the second set of failure modes; receive the diagnostic association data, wherein the diagnostic association data specifies, for each of the first set of failure modes, one or more diagnostic trouble code(s) (DTC(s)) that are to be associated with the failure mode; receive the vehicle operation signals association data, wherein the vehicle operation signals association data specifies, for each of the second set of failure modes, vehicle operation signals data that is to be associated with the failure mode; generate the augmented DFMEA data; and provide the augmented DFMEA data to the one or more computers of the vehicle fault diagnosis and analysis system.
 19. The vehicle fault diagnosis and analysis system of claim 18, wherein the one or more remote computers are separate from the one or more computers of the vehicle fault diagnosis and analysis system.
 20. The vehicle fault diagnosis and analysis system of claim 19, wherein the vehicle fault diagnosis and analysis system is controlled by an original equipment manufacturer (OEM) of the one or more vehicles, wherein the DFMEA augmentation application is provided by the OEM to a supplier that provides parts to the OEM for the one or more vehicles, and wherein the supplier controls the one or more remote computers. 